基于模糊聚类分析—BP神经网络法的平缓硬质岩斜坡卸荷带宽度评价模型

Fuzzy Clustering Analysis and BP Neural Network Method for the Evaluation of the Width of the Unloading Zone in the Gentle Hard Rock Slope

影响平缓硬质岩斜坡卸荷带宽度的因素十分复杂,而某些因素对斜坡卸荷带宽度的影响程度又难以量化,基于此,引进坡高、坡度、岩体结构等7个因素来评价平缓硬质岩斜坡卸荷带宽度,结合甑子岩斜坡56组样本进行模糊聚类分析,剔除部分干扰样本,并在此基础上,构建了BP神经网络法的平缓硬质岩斜坡卸荷带宽度评价模型.评价结果与实测值能很好地吻合,表明基于模糊聚类分析—BP神经网络法用于平缓硬质岩斜坡卸荷带宽度的判定是有效的.

The factors that affect the width of unloading zone in gentle slope are very complex, and some factors are difficult to quantify the width of slope unloading zone, based on this, the introduction of the seven factors of high slope, slope, rock structures, etc.. evaluating hard rock width, combined with the Zhenzi rock slope group of 56 samples are processed with gentle fuzzy unloading ramp clustering analy sis, eliminating interference sampleson this basis, the BP neural network method is builded for the evaluation of the width of the unloading zone in the gentle slope. The evaluation results and measured values can be a good fit, the results show that the fuzzy clustering analysis and BP neural network method is ef fective for the determination of the width of the unloading zone in gentle slope.